| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-base |
| | tags: |
| | - audio-classification |
| | - generated_from_trainer |
| | datasets: |
| | - common_language |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: wav2vec2-base-lang-id |
| | results: |
| | - task: |
| | name: Audio Classification |
| | type: audio-classification |
| | dataset: |
| | name: common_language |
| | type: common_language |
| | config: full |
| | split: validation |
| | args: full |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7800611413043478 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # wav2vec2-base-lang-id |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_language dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2554 |
| | - Accuracy: 0.7801 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0003 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 1 |
| | - seed: 0 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10.0 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 2.58 | 0.9989 | 693 | 2.5609 | 0.2899 | |
| | | 1.8581 | 1.9989 | 1386 | 2.1486 | 0.4008 | |
| | | 1.3784 | 2.9989 | 2079 | 1.5906 | 0.5666 | |
| | | 0.976 | 3.9989 | 2772 | 1.4036 | 0.6318 | |
| | | 0.6109 | 4.9989 | 3465 | 1.3022 | 0.6695 | |
| | | 0.4357 | 5.9989 | 4158 | 1.2386 | 0.7138 | |
| | | 0.23 | 6.9989 | 4851 | 1.3078 | 0.7221 | |
| | | 0.1461 | 7.9989 | 5544 | 1.2247 | 0.7534 | |
| | | 0.0567 | 8.9989 | 6237 | 1.3279 | 0.7646 | |
| | | 0.0375 | 9.9989 | 6930 | 1.2554 | 0.7801 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.49.0.dev0 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| | |
